Interictal EEG Denoising using Independent Component Analysis and Empirical Mode Decomposition

被引:0
|
作者
Salsabili, Sina [1 ]
Sardoui, Sepideh Hajipour [2 ]
Shamsollahi, Mohammad B. [2 ]
机构
[1] Sharif Univ Technol, Sch Engn & Sci, Int Campus Kish Isl, Tehran, Iran
[2] Sharif Univ Technol, Sch Elect Engn, Biomed Signal & Image Proc Lab BiSIPL, Tehran, Iran
关键词
Single Channel ICA; Multi-channel ICA denoising; EMD; Interictal Epileptic Spikes; Muscle artifact; EEG background activity;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Noise contamination is inevitable in biomedical recordings. In some cases biomedical recordings are highly contaminated with artifacts which make the effective recovering process hard to achieve. Many different methods have been proposed for artifact removal from biomedical signals but introducing an effective method which can present valuable data for medical analysis, is still an ongoing process. In this paper a new method for interictal EEG denoising is presented. Single channel ICA denoising method based on EMD decomposition is used to improve the multi-channel ICA denoising results. This method is tested on simulated epileptic recordings which are contaminated with real muscle artifact and EEG background activity.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] An EEG signal denoising method based on ensemble empirical mode decomposition and independent component analysis
    Sun, Huimin
    Cheng, Jun
    Ma, Zheng
    2018 IEEE INTERNATIONAL CONFERENCE ON CYBORG AND BIONIC SYSTEMS (CBS), 2018, : 401 - 405
  • [2] Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating
    Wang, Wen-Bo
    Zhang, Xiao-Dong
    Chang, Yuchan
    Wang, Xiang-Li
    Wang, Zhao
    Chen, Xi
    Zheng, Lei
    CHINESE PHYSICS B, 2016, 25 (01)
  • [3] Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating
    王文波
    张晓东
    常毓禅
    汪祥莉
    王钊
    陈希
    郑雷
    Chinese Physics B, 2016, (01) : 404 - 410
  • [4] Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating
    Wang, Wen-Bo
    Zhang, Xiao-Dong
    Chang, Yuchan
    Wang, Xiang-Li
    Wang, Zhao
    Chen, Xi
    Zheng, Lei
    Chinese Physics B, 2015, 25 (01)
  • [5] Chaotic signal denoising method based on independent component analysis and empirical mode decomposition
    Wang Wen-Bo
    Zhang Xiao-Dong
    Wang Xiang-Li
    ACTA PHYSICA SINICA, 2013, 62 (05)
  • [6] Pulsar Signal Denoising Method Based on Empirical Mode Decomposition and Independent Component Analysis
    Wang, Lu
    Zhang, Shuang
    Lu, Fuguo
    2018 CHINESE AUTOMATION CONGRESS (CAC), 2018, : 3218 - 3221
  • [7] A Radio Grid Monitoring Method Based on Independent Component Analysis with Empirical Mode Decomposition Denoising
    Zhang, Jingshu
    Yue, Yu
    Li, Dou
    Yang, Yanjun
    Zhao, Yuping
    2018 IEEE 3RD INTERNATIONAL CONFERENCE ON COMMUNICATION AND INFORMATION SYSTEMS (ICCIS), 2018, : 127 - 131
  • [8] Data analysis using a combination of independent component analysis and empirical mode decomposition
    Lin, Shih-Lin
    Tung, Pi-Cheng
    Huang, Norden E.
    PHYSICAL REVIEW E, 2009, 79 (06):
  • [9] Application of independent component analysis in empirical mode decomposition
    Chen, Jian-Guo
    Zhang, Zhi-Xin
    Guo, Zheng-Gang
    Weng, Feng-Fao
    Li, Hong-Kun
    Zhendong yu Chongji/Journal of Vibration and Shock, 2009, 28 (01): : 109 - 111
  • [10] The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition
    Wang, Gang
    Teng, Chaolin
    Li, Kuo
    Zhang, Zhonglin
    Yan, Xiangguo
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2016, 20 (05) : 1301 - 1308